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Article: Performance analysis of SIMO space-time scheduling with convex utility function: Zero-forcing linear processing

TitlePerformance analysis of SIMO space-time scheduling with convex utility function: Zero-forcing linear processing
Authors
KeywordsFairness
Genetic algorithm (GA)
Multiple antenna
Optimal algorithm
Scheduling
Single-input-multiple-output (SIMO)
Utility functions
Issue Date2004
PublisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25
Citation
Ieee Transactions On Vehicular Technology, 2004, v. 53 n. 2, p. 339-350 How to Cite?
AbstractIn a multiple-antenna system, an optimized design across the link and scheduling layers is crucial toward fully exploiting the temporal and spatial dimensions of the communication channel. In this paper, based on discrete optimization techniques, we derive a novel analytical framework for designing optimal space-time scheduling algorithms with respect to general convex utility functions. We focus on the reverse link (i.e., client to base station) and assume that the mobile terminal has a single transmit antenna while the base station has nR receive antennas. In order that our proposed framework is practicable and can be implemented with a reasonable cost in a real environment, we further assume that the physical layer involves only linear-processing complexity in separating signals from different users. As an illustration of the efficacy of our proposed analytical design framework, we apply the framework to two commonly used system utility functions, namely maximal throughput and proportional fair. We then devise an optimal scheduling algorithm based on our design framework. However, in view of the formidable time complexity of the optimal algorithm, we propose two fast practical scheduling techniques, namely the greedy algorithm and the genetic algorithm (GA). The greedy algorithm, which is similar to the one widely used in 3G1X and Qualcomm high-data-rate (HDR) systems (optimal when nR = 1), exhibits significantly inferior performance when nR > 1 as compared with the optimal approach. On the other hand, the GA is quite promising in terms of performance complexity tradeoff, especially for a system with a large number of users with even a moderately large nR. As a case in point, for a system with 20 users and nR = 4, the GA is more than 36 times faster than the optimal while the performance degradation is less than 10%, making it an attractive choice in the practical implementation for real-time link scheduling.
Persistent Identifierhttp://hdl.handle.net/10722/42974
ISSN
2015 Impact Factor: 2.243
2015 SCImago Journal Rankings: 1.203
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLau, VKNen_HK
dc.contributor.authorKwok, YKen_HK
dc.date.accessioned2007-03-23T04:35:49Z-
dc.date.available2007-03-23T04:35:49Z-
dc.date.issued2004en_HK
dc.identifier.citationIeee Transactions On Vehicular Technology, 2004, v. 53 n. 2, p. 339-350en_HK
dc.identifier.issn0018-9545en_HK
dc.identifier.urihttp://hdl.handle.net/10722/42974-
dc.description.abstractIn a multiple-antenna system, an optimized design across the link and scheduling layers is crucial toward fully exploiting the temporal and spatial dimensions of the communication channel. In this paper, based on discrete optimization techniques, we derive a novel analytical framework for designing optimal space-time scheduling algorithms with respect to general convex utility functions. We focus on the reverse link (i.e., client to base station) and assume that the mobile terminal has a single transmit antenna while the base station has nR receive antennas. In order that our proposed framework is practicable and can be implemented with a reasonable cost in a real environment, we further assume that the physical layer involves only linear-processing complexity in separating signals from different users. As an illustration of the efficacy of our proposed analytical design framework, we apply the framework to two commonly used system utility functions, namely maximal throughput and proportional fair. We then devise an optimal scheduling algorithm based on our design framework. However, in view of the formidable time complexity of the optimal algorithm, we propose two fast practical scheduling techniques, namely the greedy algorithm and the genetic algorithm (GA). The greedy algorithm, which is similar to the one widely used in 3G1X and Qualcomm high-data-rate (HDR) systems (optimal when nR = 1), exhibits significantly inferior performance when nR > 1 as compared with the optimal approach. On the other hand, the GA is quite promising in terms of performance complexity tradeoff, especially for a system with a large number of users with even a moderately large nR. As a case in point, for a system with 20 users and nR = 4, the GA is more than 36 times faster than the optimal while the performance degradation is less than 10%, making it an attractive choice in the practical implementation for real-time link scheduling.en_HK
dc.format.extent784508 bytes-
dc.format.extent26112 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/msword-
dc.languageengen_HK
dc.publisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25en_HK
dc.relation.ispartofIEEE Transactions on Vehicular Technologyen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectFairnessen_HK
dc.subjectGenetic algorithm (GA)en_HK
dc.subjectMultiple antennaen_HK
dc.subjectOptimal algorithmen_HK
dc.subjectSchedulingen_HK
dc.subjectSingle-input-multiple-output (SIMO)en_HK
dc.subjectUtility functionsen_HK
dc.titlePerformance analysis of SIMO space-time scheduling with convex utility function: Zero-forcing linear processingen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0018-9545&volume=53&issue=2&spage=339&epage=350&date=2004&atitle=Performance+analysis+of+SIMO+space-time+scheduling+with+convex+utility+function:+zero-forcing+linear+processingen_HK
dc.identifier.emailKwok, YK:ykwok@eee.hku.hken_HK
dc.identifier.authorityKwok, YK=rp00128en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TVT.2004.823507en_HK
dc.identifier.scopuseid_2-s2.0-1942485973en_HK
dc.identifier.hkuros91517-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-1942485973&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume53en_HK
dc.identifier.issue2en_HK
dc.identifier.spage339en_HK
dc.identifier.epage350en_HK
dc.identifier.isiWOS:000220452400006-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLau, VKN=7005811464en_HK
dc.identifier.scopusauthoridKwok, YK=7101857718en_HK

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